PSVII-21 Revision of the model estimating real-time Lys requirements in individual growing-finishing pigs
Bibliographic record
Abstract
Abstract The objective of this study was to review the calibration of the model estimating real-time Lys requirements individual in growing-finishing pigs. Two 28 d growth experiments were performed with 110 pigs distributed in a complete randomized design with growing (25 kg BW ± 2.1, n = 60; 10 pigs per treatment) and finishing (68 kg BW ± 1.8, n = 60; 10 pigs per treatment) barrows. Pigs were fed with 60, 70, 80, 90, 100, or 110% of the pig’s estimated individual standardized ileal digestible (SID) Lys (SIDLys) requirements. Body composition was measured by dual-energy X-ray densitometry on days 1 and 28 of the trial. Pigs were housed in the same pen but fed individually using computerized feeding stations. The Mixed and NLIN procedures of SAS were used to analyze the data and estimate optimal SIDLys requirements. In the growing and finishing trials protein in gain (17 to 19%; 13 to 16%) and N efficiency (52 to 65%; 40 to 55%) increased linearly (P < 0.01) with the increasing levels of SIDLys. Maximum ADG (0.98 kg/d) and protein deposition (PD; 170 g/d) were observed in growing pigs fed at 100% of the estimated SIDLys requirements (P < 0.001). Finishing pigs had maximal ADG (1.2 kg/d) when fed at 100% of the estimated SIDLys requirements, but PD increased linearly (P < 0.05) with SIDLys levels without reaching a plateau at the higher levels of Lys intake. The proposed model correctly estimates the level of SIDLys that maximizes PD and ADG in growing (25 to 50 kg of BW), and ADG in finishing pigs (65 to 100 kg BW); still, there is an opportunity for increasing PD in older pigs fed using precision feeding techniques.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".